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and Introduction Data Collection
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CHAPTER 1: INTRODUCTION AND DATA COLLECTION
1. The process of using sample statistics to draw conclusions about true population parameters is called a) statistical inference. b) the scientific method. c) sampling. d) descriptive statistics.
TYPE: MC DIFFICULTY: Easy KEYWORDS: inferential statistics 2. Those methods involving the collection, presentation, and characterization of a set of data in order to properly describe the various features of that set of data are called a) statistical inference. b) the scientific method. c) sampling. d) descriptive statistics. TYPE: MC DIFFICULTY: Easy KEYWORDS: descriptive statistics 3. The collection and summarization of the socioeconomic and physical characteristics of the employees of a particular firm is an example of a) inferential statistics. b) descriptive statistics. c) a parameter. d) a statistic. TYPE: MC DIFFICULTY: Easy KEYWORDS: descriptive statistics 4. The estimation of the population average family expenditure on food based on the sample average expenditure of 1,000 families is an example of a) inferential statistics. b) descriptive statistics. c) a parameter. d) a statistic. TYPE: MC DIFFICULTY: Easy KEYWORDS: inferential statistics
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Introduction and Data Collection 5. The universe or "totality of items or things" under consideration is called a) a sample. b) a population. c) a parameter. d) a statistic. TYPE: MC DIFFICULTY: Easy KEYWORDS: population 6. The portion of the universe that has been selected for analysis is called a) a sample. b) a frame. c) a parameter. d) a statistic.
TYPE: MC DIFFICULTY: Easy KEYWORDS: sample 7. A summary measure that is computed to describe a characteristic from only a sample of the population is called a) a parameter. b) a census. c) a statistic. d) the scientific method. TYPE: MC DIFFICULTY: Easy KEYWORDS: statistic 8. A summary measure that is computed to describe a characteristic of an entire population is called a) a parameter. b) a census. c) a statistic. d) the scientific method. TYPE: MC DIFFICULTY: Easy KEYWORDS: parameter 9. Which of the following is most likely a population as opposed to a sample? a) respondents to a newspaper survey b) the first 5 students completing an assignment c) every third person to arrive at the bank d) registered voters in a county
Introduction and Data Collection TYPE: MC DIFFICULTY: Moderate KEYWORDS: population, sample 10. Which of the following is most likely a parameter as opposed to a statistic? a) the average score of the first five students completing an assignment b) the proportion of females registered to vote in a county c) the average height of people randomly selected from a database d) the proportion of trucks stopped yesterday that were cited for bad brakes TYPE: MC DIFFICULTY: Moderate KEYWORDS: parameter, statistic 11. Which of the following is not an element of descriptive statistical problems? a) an inference made about the population based on the sample b) the population or sample of interest c) tables, graphs, or numerical summary tools d) identification of patterns in the data TYPE: MC DIFFICULTY: Moderate KEYWORDS: descriptive statistics
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12. A study is under way in Yosemite National Forest to determine the adult height of American
pine trees. Specifically, the study is attempting to determine what factors aid a tree in reaching heights greater than 60 feet tall. It is estimated that the forest contains 25,000 adult American pines. The study involves collecting heights from 250 randomly selected adult American pine trees and analyzing the results. Identify the population from which the study was sampled. a) the 250 randomly selected adult American pine trees b) the 25,000 adult American pine trees in the forest c) all the adult American pine trees taller than 60 feet d) all American pine trees, of any age, in the forest TYPE: MC DIFFICULTY: Moderate KEYWORDS: population, sample
13. A study is under way in Yosemite National Forest to determine the adult height of American
pine trees. Specifically, the study is attempting to determine what factors aid a tree in reaching heights greater than 60 feet tall. It is estimated that the forest contains 25,000 adult American pines. The study involves collecting heights from 250 randomly selected adult American pine trees and analyzing the results. Identify the variable of interest in the study a) the age of an American pine tree in Yosemite National Forest b) the height of an American pine tree in Yosemite National Forest c) the number of American pine trees in Yosemite National Forest d) the species of trees in Yosemite National Forest
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Introduction and Data Collection TYPE: MC DIFFICULTY: Easy KEYWORDS: data, sampling 14. A study is under way in Yosemite National Forest to determine the adult height of American pine trees. Specifically, the study is attempting to determine what factors aid a tree in reaching heights greater than 60 feet tall. It is estimated that the forest contains 25,000 adult American pines. The study involves collecting heights from 250 randomly selected adult American pine trees and analyzing the results. Identify the sample in the study. a) the 250 randomly selected adult American pine trees b) the 25,000 adult American pine trees in the forest c) all the adult American pine trees taller than 60 feet d) all American pine trees, of any age, in the forest TYPE: MC DIFFICULTY: Easy KEYWORDS: population, sample 15. Most analysts focus on the cost of tuition as the way to measure the cost of a college education. But incidentals, such as textbook costs, are rarely considered. A researcher at Drummand University wishes to estimate the textbook costs of first-year students at Drummand. To do so, she monitored the textbook cost of 250 first-year students and found that their average textbook cost was $300 per semester. Identify the population of interest to the researcher. a) all Drummand University students b) all college students c) all first-year Drummand University students d) the 250 students that were monitored TYPE: MC DIFFICULTY: Easy KEYWORDS: population, sample 16. Most analysts focus on the cost of tuition as the way to measure the cost of a college education. But incidentals, such as textbook costs, are rarely considered. A researcher at Drummand University wishes to estimate the textbook costs of first-year students at Drummand. To do so, she monitored the textbook cost of 250 first-year students and found that their average textbook cost was $300 per semester. Identify the variable of interest to the researcher a) the textbook cost of first-year Drummand University students b) the year in school of Drummand University students c) the age of Drummand University students d) the cost of incidental expenses of Drummand University students TYPE: MC DIFFICULTY: Easy KEYWORDS: data, sampling 17. Most analysts focus on the cost of tuition as the way to measure the cost of a college education. But incidentals, such as textbook costs, are rarely considered. A researcher at Drummand University wishes to estimate the textbook costs of first-year students at Drummand. To do so, she monitored the textbook cost of 250 first-year students and found that their average textbook cost was $300 per semester. Identify the sample in the study.
Introduction and Data Collection
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a) all Drummand University students
b) all college students c) all first-year Drummand University students d) the 250 students that were monitored TYPE: MC DIFFICULTY: Easy KEYWORDS: population, sample 18. Researchers suspect that the average number of units earned per semester by college students is rising. A researcher at Calendula College wishes to estimate the number of units earned by students during the spring semester at Calendula. To do so, he randomly selects 100 student transcripts and records the number of units each student earned in the spring term. He found that the average number of semester units completed was 12.96 units per student. Identify the population of interest to the researcher. a) all Calendula College students b) all college students c) all Calendula College students enrolled in the spring d) all college students enrolled in the spring TYPE: MC DIFFICULTY: Moderate KEYWORDS: population, sample 19. The average number of units earned per semester by college students is suspected to be rising. A researcher at Calendula College wishes to estimate the number of units earned by students during the spring semester at Calendula. To do so, he randomly selects 100 student transcripts and records the number of units each student earned in the spring term. Identify the variable of interest to the researcher. a) the number of students enrolled at Calendula College during the spring term b) the average indebtedness of Calendula College students enrolled in the spring c) the age of Calendula College students enrolled in the spring d) the number of units earned by Calendula College students during the spring term TYPE: MC DIFFICULTY: Easy KEYWORDS: data, sampling 20. Jared was working on a project to look at global warming and accessed an Internet site where he captured average global surface temperatures from 1866. Which of the four methods of data collection was he using? a) published sources b) experimentation c) surveying d) observation TYPE: MC DIFFICULTY: Easy
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Introduction and Data Collection KEYWORDS: sources of data 21. The British Airways Internet site provides a questionnaire instrument that can be answered electronically. Which of the 4 methods of data collection is involved when people complete the questionnaire? a) published sources b) experimentation c) surveying d) observation TYPE: MC DIFFICULTY: Easy KEYWORDS: sources of data 22. A marketing research firm, in conducting a comparative taste test, provided three types of peanut butter to a sample of households randomly selected within the state. Which of the 4 methods of data collection is involved when people are asked to compare the three types of peanut butter? a) published sources b) experimentation c) surveying d) observation TYPE: MC DIFFICULTY: Easy KEYWORDS: sources of data
23. Tim was planning for a meeting with his boss to discuss a raise in his annual salary. In
preparation, he wanted to use the Consumer Price Index to determine the percentage increase in his real (inflation-adjusted) salary over the last three years. Which of the 4 methods of data collection was involved when he used the Consumer Price Index? a) published sources b) experimentation c) surveying d) observation TYPE: MC DIFFICULTY: Easy KEYWORDS: sources of data 24. Which of the 4 methods of data collection is involved when a person counts the number of cars passing designated locations on the Los Angeles freeway system? a) published sources b) experimentation c) surveying d) observation TYPE: MC DIFFICULTY: Moderate
Introduction and Data Collection KEYWORDS: sources of data 25. A statistics student found a reference in the campus library that contained the median family incomes for all 50 states. She would report her data as being collected using a) a designed experiment. b) observational data. c) a random sample. d) a published source. TYPE: MC DIFFICULTY: Easy KEYWORDS: sources of data
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26. The personnel director at a large company studied the eating habits of the companys employees. The director noted whether employees brought their own lunches to work, ate at the company cafeteria, or went out to lunch. The goal of the study was to improve the food service at the company cafeteria. This type of data collection would best be considered as a) an observational study. b) a designed experiment. c) a random sample. d) a quota sample. TYPE: MC DIFFICULTY: Easy KEYWORDS: sources of data 27. A study attempted to estimate the proportion of Florida residents who were willing to spend more tax dollars on protecting the beaches from environmental disasters. Twenty-five hundred Florida residents were surveyed. What type of data collection procedure was most likely used to collect the data for this study? a) a designed experiment b) a published source c) a random sample d) observational data TYPE: MC DIFFICULTY: Easy KEYWORDS: sources of data 28. Which of the following is a discrete quantitative variable? a) the Dow Jones Industrial average b) the volume of water released from a dam c) the distance you drove yesterday. d) the number of employees of an insurance company TYPE: MC DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data
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Introduction and Data Collection 29. Which of the following is a continuous quantitative variable? a) the color of a students eyes b) the number of employees of an insurance company c) the amount of milk produced by a cow in one 24-hour period d) the number of gallons of milk sold at the local grocery store yesterday TYPE: MC DIFFICULTY: Easy KEYWORDS: continuous random variable, types of data
30. To monitor campus security, the campus police office is taking a survey of the number of
students in a parking lot each 30 minutes of a 24-hour period with the goal of determining when patrols of the lot would serve the most students. If X is the number of students in the lot each period of time, then X is an example of a) a categorical random variable. b) a discrete random variable. c) a continuous random variable. d) a statistic. TYPE: MC DIFFICULTY: Moderate KEYWORDS: discrete random variable, types of data
31. Researchers are concerned that the weight of the average American school child is increasing
implying, among other things, that childrens clothing should be manufactured and marketed in larger sizes. If X is the weight of school children sampled in a nationwide study, then X is an example of a) a categorical random variable. b) a discrete random variable. c) a continuous random variable. d) a parameter. TYPE: MC DIFFICULTY: Moderate KEYWORDS: continuous random variable, types of data 32. The classification of student class designation (freshman, sophomore, junior, senior) is an example of a) a categorical random variable. b) a discrete random variable. c) a continuous random variable. d) a parameter. TYPE: MC DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 33. The classification of student major (accounting, economics, management, marketing, other) is an example of
Introduction and Data Collection a) b) c) d) a categorical random variable. a discrete random variable. a continuous random variable. a parameter.
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TYPE: MC DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data
34. The chancellor of a major university was concerned about alcohol abuse on her campus and
wanted to find out the proportion of students at her university who visited campus bars on the weekend before the final exam week. Her assistant took a random sample of 250 students. The total number of students in the sample who visited campus bars on the weekend before the final exam week is an example of a) a categorical random variable. b) a discrete random variable. c) a continuous random variable. d) a parameter. TYPE: MC DIFFICULTY: Moderate KEYWORDS: discrete random variable, types of data
35. The chancellor of a major university was concerned about alcohol abuse on her campus and
wanted to find out the proportion of students at her university who visited campus bars on the weekend before the final exam week. Her assistant took a random sample of 250 students and computed the portion of students in the sample who visited campus bars on the weekend before the final exam. The portion of all students at her university who visited campus bars on the weekend before the final exam week is an example of a) a categorical random variable. b) a discrete random variable. c) a continuous random variable. d) a parameter. TYPE: MC DIFFICULTY: Moderate KEYWORDS: parameter, types of data
36. The chancellor of a major university was concerned about alcohol abuse on her campus and
wanted to find out the proportion of students at her university who visited campus bars on the weekend before the final exam week. Her assistant took a random sample of 250 students. The portion of students in the sample who visited campus bars on the weekend before the final exam week is an example of a) a categorical random variable. b) a discrete random variable. c) a parameter. d) a statistic.
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Introduction and Data Collection TYPE: MC DIFFICULTY: Moderate KEYWORDS: statistic, types of data
37. The chancellor of a major university was concerned about alcohol abuse on her campus and
wanted to find out the proportion of students at her university who visited campus bars on the weekend before the final exam week. Her assistant took a random sample of 250 students. The portion of students in the sample who visited campus bars on the weekend before the final exam week is an example of a) a categorical random variable. b) a discrete random variable. c) a continuous random variable. d) a parameter. TYPE: MC DIFFICULTY: Difficult KEYWORDS: continuous random variable, types of data TABLE 1-1 The manager of the customer service division of a major consumer electronics company is interested in determining whether the customers who have purchased a videocassette recorder made by the company over the past 12 months are satisfied with their products. 38. Referring to Table 1-1, the population of interest is a) all the customers who have bought a videocassette recorder made by the company over the past 12 months. b) all the customers who have bought a videocassette recorder made by the company and brought it in for repair over the past 12 months. c) all the customers who have used a videocassette recorder over the past 12 months. d) all the customers who have ever bought a videocassette recorder made by the company. TYPE: MC DIFFICULTY: Difficult KEYWORDS: population 39. Referring to Table 1-1, the possible responses to the question "How many videocassette recorders made by other manufacturers have you used?" are values from a a) discrete random variable. b) continuous random variable. c) categorical random variable. d) parameter. TYPE: MC DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data 40. Referring to Table 1-1, the possible responses to the question "Are you happy, indifferent, or unhappy with the performance per dollar spent on the videocassette recorder?" are values from a a) discrete numerical random variable. b) continuous numerical random variable. c) categorical random variable.
Introduction and Data Collection d) parameter. TYPE: MC DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 41. True or False: A population is the totality of items or things under consideration. TYPE: TF DIFFICULTY: Easy KEYWORDS: population 42. True or False: A sample is the portion of the universe that is selected for analysis. TYPE: TF DIFFICULTY: Easy KEYWORDS: sample 43. True or False: Problems may arise when statistically unsophisticated users who do not understand the assumptions behind the statistical procedures or their limitations are misled by results obtained from computer software. TYPE: TF DIFFICULTY: Easy KEYWORDS: statistical package 44. True or False: Managers need an understanding of statistics to be able to present and describe information accurately, draw conclusions about large populations based on small samples, improve processes, and make reliable forecasts. TYPE: TF DIFFICULTY: Easy KEYWORDS: reasons for learning statistics 45. True or False: The possible responses to the question How long have you been living at your current residence? are values from a continuous variable. TYPE: TF DIFFICULTY: Moderate KEYWORDS: continuous random variable, types of data
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46. True or False: The possible responses to the question How many times in the past three months have you visited a city park? are values from a discrete variable. TYPE: TF DIFFICULTY: Moderate KEYWORDS: discrete random variable, types of data
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Introduction and Data Collection
47. True or False: A continuous variable may take on any value within its relevant range even though the measurement device may not be precise enough to record it. TYPE: TF DIFFICULTY: Moderate KEYWORDS: continuous random variable, types of data
48. True or Faculty False: rank (professor to lecturer) is an example of discrete numerical data.
TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 49. True or False: Student grades (A to F) are an example of continuous numerical data. TYPE: TF DIFFICULTY: Moderate KEYWORDS: categorical random variables, types of data 50. True or False: The amount of coffee consumed by an individual in a day is an example of a discrete numerical variable. TYPE: TF DIFFICULTY: Moderate KEYWORDS: continuous random variables, types of data 51. True or False: A statistic is usually used to provide an estimate for a usually unobserved parameter. TYPE: TF DIFFICULTY: Moderate KEYWORDS: statistic, parameter, inferential statistics 52. True or False: A statistic is usually unobservable while a parameter is usually observable. TYPE: TF DIFFICULTY: Moderate KEYWORDS: statistic, parameter, inferential statistic 53. True or False: The answer to the question What is your favorite color? is an example of an ordinal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: nominal scale
Introduction and Data Collection
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54. True or False: The answer to the question How do you rate the quality of your business statistics course is an example of an ordinal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: ordinal scale 55. True or False: The answer to the question How many hours on average do you spend watching TV every week? is an example of a ratio scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: ratio scale 56. True or False: The answer to the question What is your sleeping bag temperature rating? is an example of a ratio scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: interval scale
57. The Human Resources Director of a large corporation wishes to develop an employee benefits
package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. All the employees in the corporation constitute the _______. ANSWER: population TYPE: FI DIFFICULTY: Easy KEYWORDS: population
58. The Human Resources Director of a large corporation wishes to develop an employee benefits
package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. The 500 employees who will participate in this study constitute the _______. ANSWER: sample TYPE: FI DIFFICULTY: Easy KEYWORDS: sample
59. The Human Resources Director of a large corporation wishes to develop an employee benefits
package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. The Director will use the data from the sample to compute _______. ANSWER: statistics TYPE: FI DIFFICULTY: Easy KEYWORDS: statistic
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Introduction and Data Collection
60. The Human Resources Director of a large corporation wishes to develop an employee benefits
package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. Information obtained from the sample will be used to draw conclusions about the true population _______. ANSWER: parameters TYPE: FI DIFFICULTY: Easy KEYWORDS: parameter
61. The Human Resources Director of a large corporation wishes to develop an employee benefits
package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. In this study, methods involving the collection, presentation, and characterization of the data are called _______. ANSWER: descriptive statistics/methods TYPE: FI DIFFICULTY: Easy KEYWORDS: descriptive statistics
62. The Human Resources Director of a large corporation wishes to develop an employee benefits
package and decides to select 500 employees from a list of all (N = 40,000) workers in order to study their preferences for the various components of a potential package. In this study, methods that result in decisions concerning population characteristics based only on the sample results are called _______. ANSWER: inferential statistics/methods TYPE: FI DIFFICULTY: Easy KEYWORDS: inferential statistics 63. Mediterranean fruit flies were discovered in California a few years ago and badly damaged the oranges grown in that state. Suppose the manager of a large farm wanted to study the impact of the fruit flies on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees were selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. The two main measures calculated each day (i.e., average number of damaged oranges per tree and proportion of trees having damaged oranges) are called _______. ANSWER: statistics TYPE: FI DIFFICULTY: Moderate KEYWORDS: statistic 64. Mediterranean fruit flies were discovered in California a few years ago and badly damaged the oranges grown in that state. Suppose the manager of a large farm wanted to study the impact of the fruit flies on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees were selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. The two main measures calculated each day (i.e., average number of damaged oranges per tree and proportion of trees having damaged oranges) may be used on a daily basis to estimate the respective true population _______.
Introduction and Data Collection
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ANSWER: parameters TYPE: FI DIFFICULTY: Easy KEYWORDS: parameters 65. Mediterranean fruit flies were discovered in California a few years ago and badly damaged the oranges grown in that state. Suppose the manager of a large farm wanted to study the impact of the fruit flies on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees were selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. In this study, drawing conclusions on any one day about the true population characteristics based on information obtained from the sample is called _______. ANSWER: inferential statistics/methods TYPE: FI DIFFICULTY: Moderate KEYWORDS: inferential statistics 66. Mediterranean fruit flies were discovered in California a few years ago and badly damaged the oranges grown in that state. Suppose the manager of a large farm wanted to study the impact of the fruit flies on the orange crops on a daily basis over a 6-week period. On each day a random sample of orange trees were selected from within a random sample of acres. The daily average number of damaged oranges per tree and the proportion of trees having damaged oranges were calculated. In this study, the presentation and characterization of the two main measures calculated each day (i.e., average number of damaged oranges per tree and proportion of trees having damaged oranges) is called _______. ANSWER: descriptive statistics/methods TYPE: FI DIFFICULTY: Moderate KEYWORDS: descriptive statistics 67. The Quality Assurance Department of a large urban hospital is attempting to monitor and evaluate patient satisfaction with hospital services. Prior to discharge, a random sample of patients is asked to fill out a questionnaire to rate such services as medical care, nursing, therapy, laboratory, food, and cleaning. The Quality Assurance Department prepares weekly reports that are presented at the Board of Directors meetings and extraordinary/atypical ratings are easy to flag. Values computed from the sample results each week are called _______. ANSWER: statistics TYPE: FI DIFFICULTY: Easy KEYWORDS: statistic 68. The Quality Assurance Department of a large urban hospital is attempting to monitor and evaluate patient satisfaction with hospital services. Prior to discharge, a random sample of patients is asked to fill out a questionnaire to rate such services as medical care, nursing, therapy, laboratory, food, and cleaning. The Quality Assurance Department prepares weekly reports that are presented at the Board of Directors meetings and extraordinary/atypical ratings are easy to flag. True population characteristics estimated from the sample results each week are called _______. ANSWER:
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Introduction and Data Collection parameters TYPE: FI DIFFICULTY: Easy KEYWORDS: parameter 69. The Commissioner of Health in New York State wanted to study malpractice litigation in New York. A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who were discharged during the year 1997. The proportion of malpractice claims filed from the sample of 31 thousand patients is a _______. ANSWER: statistic TYPE: FI DIFFICULTY: Moderate KEYWORDS: statistic 70. The Commissioner of Health in New York State wanted to study malpractice litigation in New York. A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who were discharged during the year 1997. The true proportion of malpractice claims filed from the population of 2.7 million patients is a _______. ANSWER: parameter TYPE: FI DIFFICULTY: Easy KEYWORDS: parameter 71. The Commissioner of Health in New York State wanted to study malpractice litigation in New York. A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who were discharged during the year 1997. Using the information obtained from the sample to predict population characteristics with respect to malpractice litigation is an example of _______. ANSWER: inferential statistics TYPE: FI DIFFICULTY: Moderate KEYWORDS: inferential statistics 72. The Commissioner of Health in New York State wanted to study malpractice litigation in New York. A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who were discharged during the year 1997. The collection, presentation, and characterization of the data from patient medical records are examples of _______. ANSWER: descriptive statistics/methods TYPE: FI DIFFICULTY: Easy KEYWORDS: descriptive statistics 73. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. The number of claims a person has made in the last 3 years is an example of a _______ variable. ANSWER: discrete TYPE: FI DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data
Introduction and Data Collection
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74. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. The distance a person drives in a year is an example of a _______ variable. ANSWER: continuous TYPE: FI DIFFICULTY: Easy KEYWORDS: continuous random variable, types of data 75. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. A person's age is an example of a _______ variable. ANSWER: continuous TYPE: FI DIFFICULTY: Easy KEYWORDS: continuous random variable, types of data 76. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. How long a person has been a licensed driver is an example of a _______ variable. ANSWER: continuous TYPE: FI DIFFICULTY: Moderate KEYWORDS: continuous random variable, types of data 77. An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. The number of tickets a person has received in the last 3 years is an example of a _______ variable. ANSWER: discrete TYPE: FI DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data 78. In purchasing an automobile, there are a number of variables to consider. The body style of the car (sedan, coupe, wagon, etc.) is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 79. In purchasing an automobile, there are a number of variables to consider. The classification of the car as a subcompact, compact, standard, or luxury size is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 80. In purchasing an automobile, there are a number of variables to consider. The color of the car is an example of a _______ variable.
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Introduction and Data Collection ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 81. Most colleges admit students based on their achievements in a number of different areas. Whether a student has taken any advanced placement courses is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 82. Most colleges admit students based on their achievements in a number of different areas. The grade obtained in senior level English. (A, B, C, D, or F) is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Moderate KEYWORDS: categorical random variable, types of data 83. Most colleges admit students based on their achievements in a number of different areas. The total SAT score achieved by a student is an example of a _______ numerical variable. ANSWER: discrete TYPE: FI DIFFICULTY: Moderate KEYWORDS: discrete random variable, types of data 84. The Dean of Students conducted a survey on campus. The gender of the student is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 85. The Dean of Students conducted a survey on campus. Class designation (Freshman, Sophomore, Junior, Senior) is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 86. The Dean of Students conducted a survey on campus. Major area of study is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data
Introduction and Data Collection
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87. The Dean of Students conducted a survey on campus. Average SAT score in mathematics is an example of a _______ numerical variable. ANSWER: continuous TYPE: FI DIFFICULTY: Easy KEYWORDS: continuous random variable, types of data 88. The Dean of Students conducted a survey on campus. Grade point average (GPA) is an example of a _______ numerical variable. ANSWER: continuous TYPE: FI DIFFICULTY: Easy KEYWORDS: continuous random variable, types of data 89. The Dean of Students conducted a survey on campus. Number of credits currently enrolled for is an example of a _______ numerical variable. ANSWER: discrete TYPE: FI DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data 90. The Dean of Students conducted a survey on campus. Number of clubs, groups, teams, and organizations affiliated with on campus is an example of a _______ numerical variable. ANSWER: discrete TYPE: FI DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data 91. A personal computer user survey was conducted. Computer brand primarily used is an example of a _______ variable. ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data
92. A personal computer user survey was conducted. Number of personal computers owned is an
example of a _______ variable. ANSWER: discrete TYPE: FI DIFFICULTY: Easy KEYWORDS: discrete random variable, types of data 93. A personal computer user survey was conducted. The number of years using a personal computer is an example of a _______ variable. ANSWER: continuous TYPE: FI DIFFICULTY: Moderate
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Introduction and Data Collection KEYWORDS: continuous random variable, types of data 94. A personal computer user survey was conducted. Hours of personal computer use per week is an example of a _______ variable ANSWER: continuous TYPE: FI DIFFICULTY: Moderate KEYWORDS: continuous random variable, types of data 95. A personal computer user survey was conducted. Primary word processing package used is an example of a _______ variable ANSWER: categorical TYPE: FI DIFFICULTY: Easy KEYWORDS: categorical random variable, types of data 96. A personal computer user survey was conducted. The number of computer magazine subscriptions is an example of a _______ variable. ANSWER: discrete TYPE: FI DIFFICULTY: Moderate KEYWORDS: discrete random variable, types of data 97. The type of TV one owns is an example of an ordinal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: nominal scale, ordinal scale
98. The type of TV one owns is an example of a numerical variable.
TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable 99. Whether the university is private or public is an example of a nominal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: nominal scale 100. Whether the university is private or public is an example of a categorical variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable
Introduction and Data Collection 101. Marital status is an example of an ordinal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: nominal scale, ordinal scale 102. Marital status is an example of a numerical variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable
21
103. The grade level (K-12) of a student is an example of a nominal scaled variable.
TYPE: TF DIFFICULTY: Easy KEYWORDS: nominal scale, ordinal scale
104. The grade level (K-12) of a student is an example of a numerical variable.
TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable
105. The level of satisfaction (Very unsatisfied, Fairly unsatisfied, Fairly satisfied, and Very
satisfied) in a class is an example of an ordinal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: ordinal scale
106. The level of satisfaction (Very unsatisfied, Fairly unsatisfied, Fairly satisfied, and Very
satisfied) in a class is an example of a categorical variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable
107. The quality (terrible, poor, fair, acceptable, very good and excellent) of a day care
center is an example of a nominal scaled variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: nominal scale, ordinal scale
22
Introduction and Data Collection
108. The quality (terrible, poor, fair, acceptable, very good and excellent) of a day care
center is an example of a numerical variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: categorical random variable 109. The amount of alcohol consumed by a person per week will be measured on an interval scale. TYPE: TF DIFFICULTY: Easy KEYWORDS: interval scale, ratio scale 110. The amount of alcohol consumed by a person per week is an example of a continuous variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: continuous random variable 111. The number of defective apples in a single box will be measured on an interval scale. TYPE: TF DIFFICULTY: Easy KEYWORDS: interval scale, ratio scale 112. The number of defective apples in a single box is an example of a continuous variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: discrete random variable, continuous random variable 113. The amount of calories contained in a pack of 12-ounce cheese will be measured on a ratio scale. TYPE: TF DIFFICULTY: Easy KEYWORDS: ratio scale 114. The amount of calories contained in a pack of 12-ounce cheese is an example of a discrete variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: discrete random variable, continuous random variable 115. The amount of time a student spent studying for an exam will be measured on a ratio scale.
Introduction and Data Collection TYPE: TF DIFFICULTY: Easy KEYWORDS: ratio scale 116. The amount of time a student spent studying for an exam is an example of a continuous variable. TYPE: TF DIFFICULTY: Easy KEYWORDS: continuous random variable 117. The date when a production line in a factor is out-of-control will be measured with a ratio scale. TYPE: TF DIFFICULTY: Easy KEYWORDS: interval scale, ratio scale
23

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CUNY Brooklyn - BUS - 30.2

26Presenting Data in Tables and ChartsCHAPTER 2: PRESENTING DATA IN TABLES AND CHARTSTABLE 2-1 An insurance company evaluates many numerical variables about a person before deciding on an appropriate rate for automobile insurance. A representative from

CUNY Brooklyn - BUS - 30.2

Numerical Descriptive Measures65CHAPTER 3: NUMERICAL DESCRIPTIVE MEASURES1. Which of the following statistics is not a measure of central tendency? a) arithmetic mean b) median c) mode d) Q3 ANSWER: d TYPE: MC DIFFICULTY: Easy KEYWORDS: measure of cent

CUNY Brooklyn - BUS - 30.2

Basic Probability91CHAPTER 4: BASIC PROBABILITY1. If two events are collectively exhaustive, what is the probability that one or the other occurs? a) 0 b) 0.50 c) 1.00 d) Cannot be determined from the information given. ANSWER: c TYPE: MC DIFFICULTY: E

CUNY Brooklyn - BUS - 30.2

Some Important Discrete Probability Distributions123CHAPTER 5: SOME IMPORTANT DISCRETE PROBABILITY DISTRIBUTIONS1. Thirty-six of the staff of 80 teachers at a local intermediate school are certified in CardioPulmonary Resuscitation (CPR). In 180 days o

CUNY Brooklyn - BUS - 30.2

The Normal Distribution and Other Continuous Distributions 153CHAPTER 6: THE NORMAL DISTRIBUTION AND OTHER CONTINUOUS DISTRIBUTIONS1. In its standardized form, the normal distribution a) has a mean of 0 and a standard deviation of 1. b) has a mean of 1

CUNY Brooklyn - BUS - 30.2

Sampling Distributions 187CHAPTER 7: SAMPLING AND SAMPLING DISTRIBUTIONS1. Sampling distributions describe the distribution of a) parameters. b) statistics. c) both parameters and statistics. d) neither parameters nor statistics. ANSWER: b TYPE: MC DIFF

CUNY Brooklyn - BUS - 30.2

224Confidence Interval EstimationCHAPTER 8: CONFIDENCE INTERVAL ESTIMATION1. The width of a confidence interval estimate for a proportion will be a) narrower for 99% confidence than for 95% confidence. b) wider for a sample size of 100 than for a sampl

CUNY Brooklyn - BUS - 30.2

Fundamentals of Hypothesis Testing: One-Sample Tests5CHAPTER 9: FUNDAMENTALS OF HYPOTHESIS TESTING: ONE-SAMPLE TESTS1. Which of the following would be an appropriate null hypothesis? a) The mean of a population is equal to 55. b) The mean of a sample i

CUNY Brooklyn - BUS - 30.2

Two-Sample Tests43CHAPTER 10: TWO-SAMPLE TESTS1. The t test for the difference between the means of 2 independent populations assumes that therespective a) sample sizes are equal. b) sample variances are equal. c) populations are approximately normal.

CUNY Brooklyn - BUS - 30.2

86Analysis of VarianceCHAPTER 11: ANALYSIS OF VARIANCE1. In a one-way ANOVA, if the computed F statistic exceeds the critical F value we may a) reject H0 since there is evidence all the means differ. b) reject H0 since there is evidence of a treatment

CUNY Brooklyn - BUS - 30.2

Chi-Square Tests and Nonparametric Tests123CHAPTER 12: CHI-SQUARE TESTS AND NONPARAMETRIC TESTS1. When testing for independence in a contingency table with 3 rows and 4 columns, there are _ degrees of freedom. a) 5 b) 6 c) 7 d) 12 ANSWER: b TYPE: MC DI

CUNY Brooklyn - BUS - 30.2

174Simple Linear RegressionCHAPTER 13: SIMPLE LINEAR REGRESSION1. The Y-intercept (b0) represents the a) predicted value of Y when X = 0. b) change in estimated average Y per unit change in X. c) predicted value of Y.d) variation around the sample reg

CUNY Brooklyn - BUS - 30.2

220Multiple Regression ModelsCHAPTER 14: INTRODUCTION TO MULTIPLE REGRESSION1. In a multiple regression problem involving two independent variables, if b1 is computed to be+2.0, it means that a) the relationship between X1 and Y is significant. b) the

CUNY Brooklyn - BIO - BIO1

26Multiple Regression Model BuildingCHAPTER 15: MULTIPLE REGRESSION MODEL BUILDING1. A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (S

CUNY Brooklyn - BUS - 30.2

Time-Series Analysis and Index Numbers47CHAPTER 16: TIME-SERIES ANALYSIS AND INDEX NUMBERS1. The effect of an unpredictable, rare event will be contained in the _ component. a) trend b) cyclical c) irregular d) seasonal ANSWER: c TYPE: MC DIFFICULTY: E

CUNY Brooklyn - BUS - 30.2

Decision Making95CHAPTER 17: DECISION MAKING1. A tabular presentation that shows the outcome for each decision alternative under the various states of nature is called: a) a payback period matrix. b) a decision matrix. c) a decision tree. d) a payoff t

CUNY Brooklyn - BUS - 30.2

124Statistical Applications in Quality and Production ManagementCHAPTER 18: STATISTICAL APPLICATIONS IN QUALITY MANAGEMENT1. The control chart a) focuses on the time dimension of a system. b) captures the natural variability in the system. c) can be us

CUNY Brooklyn - BUS - 30.2

TEST ITEM FILEStatistics for Managers Using Microsoft Excel 5th EditioniiTEST ITEM FILEStatistics for Managers Using Microsoft Excel 5th EditionDavid M. Levine, David Stephan, Timothy C. Krehbiel and Mark L. BerensoniiiivTable of ContentsPreface

CUNY Brooklyn - BIO - BIO1

;BiologyEighth EditionJonathan B. LososHarvard UniversityKenneth A. MasonPurdue UniversitySusan R. SingerCarleton Collegebased on the work ofPeter H. RavenDirector, Missouri Botanical Gardens; Engelmann Professor of Botany Washington University

CUNY Brooklyn - BIO - BIO1

part the molecular basis of lifeIThe Science of BiologyYOU ARE ABOUT TO EMBARK ON A JOURNEYa journey of discovery about the nature of life. Nearly 180 years ago, a young English naturalist named Charles Darwin set sail on a similar journey on board H.M

CUNY Brooklyn - BIO - BIO1

*16 Chapter 22The Nature of MoleculesintroductionABOUT 12.5 BILLION YEARS AGO, an enormous explosion likely marked the beginning of the universe. With this explosion began a process of star building and planetary formation that eventually led to the f

CUNY Brooklyn - BIO - BIO1

*323The Chemical Building Blocks of LifeintroductionA CUP OF WATER CONTAINS more molecules than there are stars in the sky. But many molecules aremuch larger than water molecules; they consist of thousands of atoms, forming hundreds of molecules that

CUNY Brooklyn - BIO - BIO1

*58partII Chapter 4biology of the cellCell StructureintroductionALL ORGANISMS ARE COMPOSED OF CELLS. The gossamerwing of a butterfly is a thin sheet of cells and so is the glistening outer layer of your eyes. The hamburger or tomato you eat is comp

CUNY Brooklyn - BIO - BIO1

*84Chapter 5MembranesintroductionAMONG A CELLS MOST IMPORTANT ACTIVITIES are its interactions with theenvironment, a give-and-take that never ceases. Without it, life could not persist. Living cells are encased within a lipid membrane through which f

CUNY Brooklyn - BIO - BIO1

*104Chapter 6introductionEnergy and MetabolismLIFE CAN BE VIEWED AS A CONSTANT flow of energy, channeled by organisms to do the work of living. Each of the significant properties by which we define lifeorder, growth, reproduction, responsiveness, and

CUNY Brooklyn - BIO - BIO1

*118chapter concept outline7 How Cells Harvest EnergyLIFE IS DRIVEN BY ENERGY. All the activities organisms carryoutthe swimming of bacteria, the purring of a cat, your thinking about these wordsuse energy. In this chapter, we discuss the processes al

CUNY Brooklyn - BIO - BIO1

*142Chapter 8PhotosynthesisintroductionTHE RICH DIVERSITY OF LIFE that covers our Earth would be impossible without photosynthesis. Almost every oxygen atom in the air we breathe was once part of a water molecule, liberated by photosynthesis. All the

CUNY Brooklyn - BIO - BIO1

;9chapterCell CommunicationintroductionSPRINGTIME IS A TIME OF REBIRTH and renewal. Trees thathave appeared dead produce new leaves and buds, and flowers sprout from the ground. For sufferers of seasonal allergy, this is not quite such a pleasant ti

CUNY Brooklyn - BIO - BIO1

;2.5 m10chapterHow Cells DivideintroductionALL SPECIES OF ORGANISMSbacteria, alligators, the weeds ina lawngrow and reproduce. From the smallest creature to the largest, all species produce offspring like themselves and pass on the hereditary infor

CUNY Brooklyn - BIO - BIO1

;partIII1116.6 mGenetic and Molecular BiologySexual Reproduction and Meiosischapter introductionMOST ANIMALS AND PLANTS reproduce sexually. Gametes of opposite sex unite to form a cell that,dividing repeatedly by mitosis, eventually gives rise to

CUNY Brooklyn - BIO - BIO1

;12chapterPatterns of Inheritancei ntroductionEVERY LIV I NG CREATURE IS A PRODUCT of the long evolutionary history of life on Earth. All organisms share this h istory, but as far as we know, only humans wonder about the p rocesses that led to their

CUNY Brooklyn - BIO - BIO1

;134 mmchapterChromosomes, Mapping, and the MeiosisInheritance ConnectionintroductionMENDELS EXPERIMENTS OPENED the door to understanding inheritance, but many questionsremained. In the early part of the 20th century, we did not know the nature of

CUNY Brooklyn - BIO - BIO1

;14chapterD NA: The Genetic MaterialintroductionTHE REALIZATION THAT PATTERNS OFheredity can be explained by the segregation of chromosomes in meiosis raised a question that occupied biologists for over 50 years: What is t he exact nature of the con

CUNY Brooklyn - BIO - BIO1

;151.2 mchapterGenes and How They Workconcept outlineintroduction15.1 The Nature of Geness Garrod concluded that inherited disorders can involve specific enzymes s Beadle and Tatum showed that genes specify enzymes s The central dogma describes in

CUNY Brooklyn - BIO - BIO1

;partIII16genetic and molecular biology40 mm 40 mchapterIN MUSIC, DIFFERENT INSTRUMENTS PLAY their own parts atdifferent times during a piece; a musical score determines which instruments play when. Similarly, in an organism different genes are ex

CUNY Brooklyn - BIO - BIO1

;170.3 mmchapterBiotechnologyintroductionOVER THE PAST DECADES, the development of new andpowerful techniques for studying and manipulating DNA has revolutionized biology. The knowledge gained in the last 25 years is greater than the rest of the hi

CUNY Brooklyn - BIO - BIO1

;18chapterGenomicsTHE PACE OF DISCOVERY IN BIOLOGY in the last 30 years hasbeen like the exponential growth of a population. Starting with the isolation of the first genes in the mid-1970s, researchers had accomplished the first complete genome seque

CUNY Brooklyn - BIO - BIO1

;194000 mchapterCellular Mechanisms of Developmentintroduction19.1 Overview of Development 19.2 Cell Divisions Development begins with cell division s Every cell division is known in the development of C. elegans s Stem cells continue to divide and

CUNY Brooklyn - BIO - BIO1

;partIVevolution20Genes Within Populationschapter introductionNO OTHER HUMAN BEING is exactly like you (unless you have an identical twin). Often the particular characteristics of an individual have an important bearing on its survival, on its chan

CUNY Brooklyn - BIO - BIO1

;21chapterThe Evidence for EvolutionintroductionAS WE DISCUSSED IN CHAPTER 1, when Darwin proposed his revolutionary theory of evolution bynatural selection, little actual evidence existed to bolster his case. Instead, Darwin relied on observations

CUNY Brooklyn - BIO - BIO1

;22The Origin of Specieschapteri ntroductionALTHOUGH DARWIN TITLED HIS BOOKSpecies, he never actually discussed what he referred to as that mystery of mysterieshow one species gives rise to another. Rather, his argument concerned evolution by natura

CUNY Brooklyn - BIO - BIO1

;chapter23Systematics and the Phylogenetic RevolutionintroductionALL ORGANISMS SHARE MANY biological characteristics.Theyare composed of one or more cells, carry out metabolism and transfer energy with ATP, and encode hereditary information in DNA.

CUNY Brooklyn - BIO - BIO1

;24Genome EvolutionintroductionGENOMES CONTAIN THE RAW MATERIALhidden in the ever-changing nature of genomes. As more genomes have been sequenced, the new and exciting field of comparative genomics has emerged and has yielded some surprising results

CUNY Brooklyn - BIO - BIO1

;25chapterEvolution of Developmenti ntroductionHOW IS IT THAT CLOSELYrelated species of frogs can have completely different patterns of development? One frog goes f rom fertilized egg to adult frog with no intermediate tadpole stage. The sister spec

CUNY Brooklyn - BIO - BIO1

;partVdiversity of life on earth26IN PRECEDING CHAPTERS, youve seen that many commonfeatures are found in living things. To name a few, they are composed of one or more cells, they carry out metabolism and transfer energy with ATP, and they encode h

CUNY Brooklyn - BIO - BIO1

;27.036 mm .036 mchapterV irusesintroductionWE BEGIN OUR EXPLORATIO N of the diversity of life with v iruses. Viruses are genetic elements enclosed in protein; they a re not considered organisms since they lack many of the features associated with l

CUNY Brooklyn - BIO - BIO1

;28chapterProkaryotesintroductionONE OF THE HALLMARKS OF LIVING organisms is their cellular organization. You learned earlier that living things come in two basic cell types: tp`twdv and d xp`twdvTo review, prokaryotes lack the membrane-bounded nucl

CUNY Brooklyn - BIO - BIO1

;29FOR MORE THAN HALF OF the long history of life on Earth, all life was microscopic. The biggestorganisms that existed for over 2 billion years were single-celled bacteria fewer than 6 mm thick. These prokaryotes lacked internal membranes, except for

CUNY Brooklyn - BIO - BIO1

;30Overview of Green PlantsintroductionchapterPLANT EVOLUTION IS THE STORY of adaptation to terrestriallife by green algal ancestors. All green algae and land plants share a common ancestor, composing a monophyletic group called the green plants. Fo

CUNY Brooklyn - BIO - BIO1

;31chapterFungiintroductionTHE FUNGI, AN OFTEN-OVERLOOKED group of unicellular and multicellular organisms, have aprofound influence on ecology and human health. Along with bacteria, they are important decomposers and disease-causing organisms. Fung

CUNY Brooklyn - BIO - BIO1

;32chapter introductionOverview of Animal DiversityWE NOW EXPLORE THE GREAT diversity of modern animals,the result of a long evolutionary history. Animals are among the most abundant living organisms. Found in almost every conceivable habitat, they b

CUNY Brooklyn - BIO - BIO1

;33chapterNoncoelomate InvertebratesintroductionWE START OUR EXPLORATION of the great diversity of animals with the simplest members of theanimal kingdomsponges, jellyfish, and simple worms. These animals lack a body cavity(coelom), and they are th

CUNY Brooklyn - BIO - BIO1

;34chapterCoelomate InvertebratesALTHOUGH ACOELOMATES AND PSEUDOCOELOMATEShave proven very successful, a third way of organizing the animal body has also evolved, one that occurs in many protostomes and in all deuterostomes. We begin our discussion o

CUNY Brooklyn - BIO - BIO1

;35chapter introductionMEMBERS OF THE PHYLUM CHORDATA exhibit great changes in the endoskeleton compared with what is seen in echinoderms. As you saw in chapter 34, the endoskeleton of echinoderms is functionally similar to the exoskeleton of arthropod

CUNY Brooklyn - BIO - BIO1

;partVIplant form and function36chapterPlant FormintroductionALTHOUGH THE SIMILARITIES AMONG a cactus, an orchid, anda hardwood tree might not be obvious at first sight, most plants have a basic unity of structure. This unity is reflected in how

CUNY Brooklyn - BIO - BIO1

;37chapterVegetative Plant DevelopmentintroductionHOW DOES A FERTILIZED EGG DEVELOP into a complex adultplant body? Because plant cells cannot move, the timing and directionality of each cell division must be carefully orchestrated. Cells need infor

CUNY Brooklyn - BIO - BIO1

;chapter38T ransport in PlantsintroductionTERRESTRIAL PLANTS FACE TWOmajor challenges: maintaining water and n utrient balance, and providing sufficient structural support for upright growth. The vascular system t ransports water, minerals, and orga

CUNY Brooklyn - BIO - BIO1

;39chapterPlant Nutrition and SoilsVAST ENERGY INPUTS ARE REQUIRED for the ongoingconstruction of a plant. In this chapter, youll learn what inputs, besides energy from the Sun, a plant needs to survive. Plants, like animals, need various nutrients t

CUNY Brooklyn - BIO - BIO1

;40chapterPlant Defense ResponsesPLANTS ARE CONSTANTLY UNDER ATTACK by viruses,bacteria, fungi, animals, and even other plants. An amazing array of defense mechanisms has evolved to block or temper an invasion. Many plantpest relationships undergo co

CUNY Brooklyn - BIO - BIO1

;41chapterALL ORGANISMS SENSE AND INTERACT with their environments. This is particularly true ofplants. Plant survival and growth are critically influenced by abiotic factors, including water, wind, and light. The effect of the local environment on pl

CUNY Brooklyn - BIO - BIO1

;42chapterPlant ReproductionintroductionTHE REMARKABLE EVOLUT IONARY SUCCESS of floweringp lants can be linked to their novel reproductive strategies. In t his chapter, we explore the reproductive strategies of the angiosperms and how their unique f